A Novel eFace System to Prevent the Risks of Facial Distortion after CMF Surgery

新型 eFace 系统可预防 CMF 手术后面部变形的风险

• 批准号: 8439794
• 负责人: James J Xia
• 金额: $ 38.78万
• 依托单位: METHODIST HOSPITAL RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-05-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8439794
• 关键词: Address; Aging; Algorithms; Anatomy; Appearance; Clinical; Complex; Data; Defect; Deformity; Development; Elements; Face; Figs - dietary; Forensic Sciences; Goals; Growth; Histocompatibility Testing; Imagination; Individual; Laboratories; Learning; Left; Machine Learning; Maps; Mechanics; Methods; Modeling; Operative Surgical Procedures; Orthodontics; Osteotomy; Outcome; Patient Education; Patients; Plastic Surgical Procedures; Plastics; Postoperative Period; Property; Reconstructive Surgical Procedures; Reporting; Residual state; Risk; Running; Severities; Simulate; Skeleton; Speed; Statistical Models; Surgeon; System; Techniques; Testing; Thick; Time; Tissues; Training; Variant; Visual; balance testing; base; bone; craniomaxillofacial; experience; imaging informatics; improved; improved functioning; innovation; meetings; novel; open source; prevent; psychologic; public health relevance; reconstruction; simulation; skeletal; skeletal surgery; soft tissue; system architecture; virtual

DESCRIPTION (provided by applicant): The number of patients suffering from craniomaxillofacial (CMF) deformities and requiring surgical correction is escalating. CMF deformities may involve skeleton, overlying soft-tissues, or the both. Patients with CMF deformities often have psychological problems. The goal of CMF surgery is to reconstruct a normal facial appearance and function, and the outcome of the surgery is judged as such. The current problem is that we do not have a reliable way of simulating the soft-tissue-change following skeletal reconstruction. In treating patients with isolated skeletal defects, the current practice is to normalize the skeleton, hoping for optimal facial appearance. However, because the thickness and contour of the soft-tissue envelope varies from patient to patient, this approach is not reliable. The problem is even bigger in patients with composite defects. For example, in the scenario of a patient with a skeletal deformity and a mild soft-tissue defect, a surgeon would have to know, before surgery, how to overcorrect the skeleton to camouflage the soft-tissue defect. But, this information can only be attained by having an accurate planning system to simulate soft-tissue changes. In addition, from patient's perspective, the final facial appearance is the most apparent to them. Therefore, it is extremely important, for both doctors and patients, to accurately simulate soft-tissue-deformation. Simulation methods must be accurate and fast. Attaining both is difficult because these attributes are inversely related, the more accurate the model, the longer it takes to prepare and run. Among the most effective, they are empirical-based model, mass spring model, finite element model, and mass tensor model. Unfortunately they are either too inaccurate or too slow, and clinically unacceptable. Our hypothesis is that facial soft-tissue changes following virtual osteotomy can be accurately simulated by our innovative approach using an anatomically detailed modeling and mapping routine, along with statistical modeling technique. To test our hypothesis, we propose to develop an open source novel imaging informatics platform, eFace system, to accurately simulate soft-tissue-change following virtual osteotomies, and thus to significantly improve the outcomes of patients undergoing facial reconstruction. This approach can not only maintain the integrity of complex facial anatomy to accurately simulate the facial soft tissue deformation, but also significantly improve the computational efficiency in order to fit the requirement for clinical use This project presents an innovative approach to model the facial soft-tissue deformation. If successful, it will allow accurate simulation of soft-tissue changes after virtual osteotomy. Patients will also be able to foresee the postoperative face preoperatively (patient education) and regain their psychological confidence. Finally, eFace will have significant impact and applications in orthodontics, plastic surgery, general surgery, growth/aging prediction, and forensic science.

描述（由申请人提供）：患有颅颌面（CMF）畸形并需要手术矫正的患者数量正在增加。CMF畸形可能涉及骨骼、覆盖软组织或两者兼而有之。CMF畸形的患者往往有心理问题。CMF手术的目标是重建正常的面部外观和功能，并以此判断手术的结果。目前的问题是，我们没有一个可靠的方法来模拟骨骼重建后的软组织变化。在治疗孤立性骨骼缺陷患者时， 练习是使骨骼正常化，希望获得最佳的面部外观。然而，由于软组织包膜的厚度和轮廓因患者而异，因此这种方法并不可靠。对于有复合缺陷的患者，这个问题甚至更大。例如，在骨骼畸形和轻度软组织缺陷的患者的情况下，外科医生必须在手术前知道如何过度矫正骨骼以掩盖软组织缺陷。但是，这些信息只能通过精确的计划系统来模拟软组织变化来获得。此外，从患者的角度来看，最终的面部外观对他们来说是最明显的。因此，准确地模拟软组织的变形对医生和患者都是非常重要的。 仿真方法必须准确和快速。两者都很难实现，因为这些属性是反向相关的，模型越精确，准备和运行的时间就越长。其中最有效的是基于材料的模型、质量弹簧模型、有限元模型和质量张量模型。不幸的是，它们要么太不准确，要么太慢，临床上不可接受。 我们的假设是，面部软组织的变化后，虚拟截骨术可以准确地模拟我们的创新方法，使用解剖学上详细的建模和映射例程，沿着与统计建模技术。为了验证我们的假设，我们建议开发一个开源的新型成像信息学平台，eFace系统，以准确地模拟虚拟截骨术后的软组织变化，从而显着改善接受面部重建的患者的结果。该方法既能保持复杂面部解剖结构的完整性，准确模拟面部软组织变形，又能显著提高计算效率，满足临床应用的要求。如果成功，它将允许准确模拟虚拟截骨术后的软组织变化。患者还将能够在术前预见术后面部（患者教育），并重新获得心理信心。最后，eFace将在整形外科、整形外科、普通外科、生长/衰老预测和法医学中产生重大影响和应用。